One problem during operation of radio receivers is represented by intersymbol interference that is introduced by the transmission channel. The channel distortion that is caused by the intersymbol interference may in poor transmission conditions be so severe that it is no longer possible to determine the correct data.
In the case of time division multiplexing methods (TDMA; Time Division Multiple Access) such as GSM (Global System for Mobile Communications) or EDGE (Enhanced Data Rates for GSM Evolution), the channel equalization process is carried out by means of so-called training sequences. In a time-division multiplexing method, the data symbols which carry the information are transmitted in successive data bursts. In order to carry out a channel estimation process, followed by channel equalization, each data burst additionally contains a training sequence, which in each case has a predetermined pseudo-random data sequence. The training sequences are likewise stored in a memory at the receiver end. The radio receiver can thus use the training sequences received from the radio transmitter and the training sequences obtained from the memory for channel estimation. The channel estimation process is carried out by calculation of so-called channel parameters or channel coefficients. In a channel equalizer, the channel parameters are used in order to reconstruct the data symbols transmitted from the radio transmitter from the signals received by the radio receiver.
A further problem during operation of radio receivers is that DC components occur in the received signal for various reasons in the radio receiver. These DC components are referred to in the following text as the DC offset (Direct Current) or as DC interference, in accordance with the conventional nomenclature. The DC interference cannot be eliminated completely, even in high-quality radio receivers, and must therefore be estimated and corrected during the baseband signal processing. Otherwise, the DC interference would adversely affect the equalization of the received signal, and would lead to an increased bit error rate in the radio receiver.
The simplest approach for estimation of the DC interference is to average two or more data bursts over the baseband symbols. However, this method often leads to very inaccurate results in the situation where the DC interference changes with each data burst. This is the situation in particular in the case of a network frequency hopping method. In the case of frequency hopping methods, the DC interference must therefore be estimated individually for each data burst. However, for example in the case of the GMSK method (Gaussian Minimum Shift Keying) and in the case of the 8-PSK method (Phase Shift Keying), for example, it is not possible to estimate the DC interference by averaging over only one data burst, since averaging over only a small number of baseband symbols is generally not equal to zero in the case of these methods. In consequence, it is not possible to distinguish between an inherently occurring discrepancy in the mean value from the zero point and DC interference which has been caused by the receiver.
A further approach for estimation of the DC interference is to represent the baseband symbols as a circle on the complex numerical plane. In this case, DC interference causes a shift in the center of the circle. This shift can be detected by determining the associated circle from the received baseband symbols using a least-squares method. This approach has the disadvantage that it cannot be used for the 8-PSK method which is used, for example, in EDGE receivers.
FIG. 1 shows the procedure for a conventional method for compensation for the DC interference and for channel equalization, in a schematic form. In this case, the DC interference on the signals received in the radio receiver is estimated first of all, and this is then compensated for. The signals which are now no longer subject to any DC interference are now used together with the training sequence to calculate the channel parameters. The channel parameters are passed to a channel equalizer, which carries out the channel equalization process.
FIG. 2 shows a further method, which is likewise known, for compensation for the DC interference and for channel equalization, in schematic form, which is described in the article “Using a direct conversion receiver in EDGE terminals: A-new DC offset compensation algorithm” by B. Lindoff, which appeared in the journal Proc. IEEE PIMRC, 2000, pages 959-963. This method allows the estimation of the DC interference as well as the channel estimation process to be carried out at the same time. The fundamental idea of the method is to regard the DC interference as an additional unknown parameter in the fundamental channel model, and to include the estimation of the DC interference in the channel estimation process. The DC interference and the channel parameters which have been determined in this way are then passed to a unit for compensation for the DC interference and to a channel equalizer. The joint estimation of the DC interference with the channel estimation can be used for all types of modulation. This method according to B. Lindoff has the disadvantage, however, that it requires a large amount of read only memory and involves a large amount of computation complexity.
The German Patent Application DE 101 37 675.8 describes a method for estimation of the DC interference and for channel estimation in a digital baseband signal in a radio receiver. In this method, the channel parameters for the channel estimation process are first of all calculated by means of a least-squares method using a training sequence that is known in the receiver, and ignoring the DC interference. The DC interference is then estimated and the channel estimation process is carried out, with correction terms for the channel parameters being calculated for the estimation process, taking into account the DC interference. This method makes use of the fact that the training sequence TSC in GSM is real, so that the majority of the so-called Fisher information matrix is real. However, this procedure still has the disadvantage that this matrix must be stored. Since a number of training sequences are defined, a set of 8 matrices must be stored. If it is intended to take into account an even greater number of channel lengths, the number of stored matrices is multiplied accordingly.